Research On Reactive Power Measurement Of Power System Based On Wavelet Analysis

With the rapid development of modern information technology and electric power industry, power system, power supply and load types have become more and more. New energy sources such as wind power, solar power and other new energy systems and some new intelligent equipment are used in power system. The extensive use of conversion device, as well as the system flow and compensate for some of the variable adjustment device is become more complex, nonlinear characteristics of power system has become increasingly clearly, a large number of non-linear loads in power system and the use of electric power network provided by the voltage and current waveform distortion are getting worse. Asymmetry of power network and load characteristics and power networks, non-linear harmonic pollution has become increasingly serious, while the power network also may be subject to some random signal interference, such as electromagnetic radiation, and some electrical equipment in operation generated stochastic, non-stationary nature of some of the interference signal, and the random signal and the frequency distribution of a wide harmonic signal in the system are very difficult to be measured accurately.Many scientist and technician have undertaken extensive research in the random signal detection and harmonic analysis, there has been a lot of literature about signal detection and harmonic processing. Solving the power quality pollution in a variety of new electrical equipment, non-linear load on the grid power system and power network analysis has become hot in the current power system research. Such as the power quality analysis, harmonic analysis of compensation device research and development, testing and compensation of reactive power, power filter design, research has achieved great development. As in the instantaneous reactive power theory-based power system reactive power detection and compensation as one of the current research focus harmonic detection gained wider application. The reactive power detection of power system is not accurate currently, this situation especially for the detection and control of power system had a significant impact in the power system, The accurate detection of active power and reactive power is not only the base of reactive power regulation, but also has a direct impact on the level of precision of detection control. At the same time with the electricity market development, electricity prices not only take into account the level of active power, but also the reactive power is taken into account in the system, so the accurate detection active and reactive power of power system is the base of energy metering and billing.A large number of theories have emerged in power system signal processing, the traditional signal processing and analysis methods have significant limitations. With the development of signal processing, Fourier transform have began to gain a wide range of applications, Fourier transform spectral characteristics analysis obtained the fundamental theoretical basis of the current electricity power harmonics detection and measurement, and solved the detection accuracy problems. But the applications of the Fourier transform in practical engineering have also encountered problems, because the power system may experience a complex random signals, using Fourier transform signal decomposition under certain conditions, will produce spectral leakage, spectrum aliasing and phenomena such as fence effect. At the same time Fourier transform is to decompose the signal according to fundamental frequency as an integer multiple of fundamental frequency harmonics, while the actual signal may exist the fundamental frequency is not an integer multiple of the inter-harmonics, which will lead to analysis results of the calculation does not correspond with reality. At the same time Fourier transform decompose signal into the superposition of sine and cosine functions and this algorithm has a large computational complexity, the actual signal analysis will occupy a lot of processor time, resulting in real-time variation. The more excellent time-frequency signal processing and analysis methods are generally decompose signal according to band division, through algorithms and filters decompose the signal into several different frequency bands, so that not only meets the requirements of the signal frequency division and also be according to the signal decomposition of time-frequency and revise the complexity of the algorithm, Compared with Fourier transform, it can adapt to the accuracy of signal processing requirements and real-time requirements and has little computation.Signal processing method based on Fourier transform and the traditional active, reactive power theory have been widely applied in the field of instrumentation and testing. In the system of increasingly complex power load and new energy power equipment, these theoretical approaches and measuring instruments based on these theories have become increasingly stretched, due to a lot of random non-stationary signals appeared in power system, the analysis and practical conclusion may be far from actuality, the signal detection accuracy is getting worse and can not cope with increasing complexity of the power system signals currently, and sometimes even come to the wrong conclusions. So it must find better time-frequency analysis theory for power system signal analysis.Wavelet transform as a relatively new method of time-frequency analysis is received attention by many scholars and it began to show its vitality in many areas. In addition to the field of image and voice access processing, it is also applied in the transient signal analysis of power system, with Wavelet transform, we can accurately analyze the characteristics of random signals, such as the transient moment of harmonic signal mutations, mutation moment and transient signal amplitude and frequency components, it also can analyze the local transient signal characteristics and calculate the statistical characteristics of random signals very precisely. It has excellent characteristics of sub frequency signal decomposition, and can separate the steady-state signal and transient signal effectively.Wavelet transform is a theory based on frequency domain of power signal and on band decomposition of signal, it is of great significance in signal analysis and processing in power grid. Using it for harmonic analysis and reactive power detection is not only the needs of power system and the electric energy metering, but its analysis and calculation results will also be the basis of reactive detection and reactive power compensation. This paper studies power system reactive power measurement theory, wavelet transform theory and algorithm based on the following research work:(1) Analyzed the widely used reactive power theory currently and several commonly used in reactive power measurement algorithm, comparatively studied the advantages and disadvantages of the power theories and algorithms based on signal processing and filter design theory. Discussed the advantages and disadvantages of Fourier transform in signal decomposition, pointed out its application scope and practical lack, In the situation of signals such as non-stationary signals and rapid change signals, Fourier transform has a fixed time-frequency window function and can not meet the demand of such signal analysis and calculation, at the same time proposed directions for improvement. In the explore process of time domain and frequency domain analysis methods of reactive power mearsurement, focused on analyzing several domestic, foreign experts, scholars on the different definitions of reactive power and the specified the stable periodic signal power decomposition and measurement theory. Analyzed the practical power theories under the conditions of the signal distortion and discussed a variety of power theory, algorithms, real physical significance and specified the scope of application.(2) Studied reactive power theory and reactive power measurement algorithm of non-sinusoidal circuit containing multi-frequency harmonic signal, through the analysis of the variety of reactive power measurement algorithm, proposed the reactive power measurement algorithm based on the reactive power definition of Budeanu non-sinusoidal circuit and based on Hilbert transform, which achieved the digital signals phase shift through a Hilbert digital filter, So it can calculate the reactive power with the active power theoretical calculation. This phase shift through the use of filtering and calculation of reactive power detection algorithm is suitable to the signal analysis and calculation which containing the harmonic signal, it is very practical for the non-sinusoidal circuit containing the multi-frequency harmonics. In this paper, filter design theory, digital filter designed by Hilbert phase shift with excellent features, have a large frequency range to achieve accurate phase shift and has a superior frequency response characteristics, such high-precision phase-shifting can substantially increase the capacity of signal harmonics decomposition and power measurement accuracy.(3) Focused on continuous wavelet transform, discrete wavelet transform and several high-performance signal processing method in the time-frequency signal processing. Analyzed the continuous wavelet transform, discrete wavelet transform time-frequency decomposition characteristics. Pointed out the limitations of Fourier transform method in time-frequency decomposition and the performance improvement is discussed about wavelet transform Compare to the Fourier transform. based on the analysis of a variety of wavelet transform and the signal characteristics of actual system we constructed the wavelet function. At the same time we researched various types of wavelet function filters compatively, such as Dmeyer wavelet, DB wavelet of different levels such as the signal processing of the different characteristics. The decomposition results were compared, and the errors and their causes are discussed by different wavelet decomposition, at the same time found the way to improve the accuracy of signal decomposition. And using the constructed wavelet filter to decompose the signal into different frequency sub-bands, the reconstruction is just a reverse process, and then the signal analysis and calculation is performed in different sub-bands respectively, got the effective value, power and other related parameters of the signal. Made an analysis of detection methods to extract signal features in the current power system by presence of non-linear, non-stationary transient signals, and derived several reactive power measurement algorithm of power system based on wavelet filter.(4) Analysis of the construction of discrete wavelet functions and their selection of quadrature mirror filter banks for signal decomposition, harmonic analysis and detection of reactive power impact on power system based on the actual signal analysis, combined with the existing wavelet function and wavelet filter design theory, constructed a new frequency-domain partial good orthogonal wavelet function, the orthogonal wavelet function is able to achieve high-precision sub-band signals and measurement of various sub-bands, which can improve measurement accuracy. At the same time systematically studied the overall structure and programs of the active and reactive power measurement based on discrete wavelet transform polyphase filter, and verified that the wavelet analysis has a dual time-domain and frequency domain resolution, the orthogonal wavelet function algorithm designed has a very good band harmonic extraction and power detection accuracy in the signal decomposition at the reactive power measurement.(5) Studied and designed the induction motor torque tester based on Wavelet transform, Analyzed and calculated the input voltage and current of induction motors by the constructed wavelet filter, therefore calculated the motor active and reactive power. Tested the motor rotate speed by infrared gun device, derived motor torque observations formula combined with the dynamic equations of induction motor, and measured the induction motor's torque.(6) Studied the existing aliasing of the discrete wavelet transform and the quadrature mirror filter bank structure conducted a, analyzed the real causes of the wavelet aliasing caused in wavelet transform, focused discused the wavelet filter amplitude-frequency characteristics and amplitude, phase errors caused by amplitude-frequency characteristics of the wavelet decomposition. Used specific wavelet function of the amplitude-frequency characteristic diagram to illustrate the wavelet-aliasing, and aliasing effects on the detection, calculated the aliasing component combined with theoretical analysis of quadrature mirror filters, and promoted the specific aliasing suppression method, using the calculated result to compensate the aliasing of the actual decomposition. Promote the wavelet function selection principle to solve detection leaks and to ensure the accuracy by the frequency characteristics of wavelet transform and the energy leakage. Analyzed the relationship between the wavelet decomposition filter sequence length and the energy leakage suggested at the wavelet function construction, promoted the wavelet filter selection method of the elimination of wavelet-aliasing and to improve detection accuracy combined with the filter amplitude-frequency characteristic, eliminated the aliasing and testing errors of traditional wavelet filter.